Deadly Environmental Governance: Authoritarianism, Eco-populism, and the Repression of Environmental and Land Defenders
Bibliographic record
Abstract
Environmental and resource governance models emphasize the importance of local community and civil society participation to achieve social equity and environmental sustainability goals. Yet authoritarian political formations often undermine such participation through violent repression of dissent. This article seeks to advance understandings of violence against environmental and community activists challenging authoritarian forms of environmental and resource governance through eco-populist struggles. Authoritarianism and populism entertain complex relationships, including authoritarian practices toward and within eco-populist movements. Examining a major agrarian conflict and the killing of a prominent Indigenous leader in Honduras, we point to the frequent occurrence of deadly repression within societies experiencing high levels of inequalities, historical marginalization of Indigenous and peasant communities, a liberalization of foreign and private investments in land-based sectors, and recent reversals in partial democratization processes taking place within a broader context of high homicidal violence and impunity rates. We conclude with a discussion of the implications of deadly repression on environmental and land defenders. Key words: authoritarianism, environmental defenders, Honduras, populism, repression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".